Value of Periodic and Aperiodic EEG Components to Detect Cognitive Deterioration

Cognitive deterioration is an important symptom of various neurological disorders. It is characterized by an impairment in memory and/or other cognitive functions compared to previous performance, leading to difficulties in daily activities and placing a burden on both families and communities. Electroencephalography (EEG), a non-invasive method, is used to monitor electrical activity in the brain. The power spectrum of EEG signals includes periodic and aperiodic components. While many studies had previously emphasized the periodic component, recent researches have concentrated on aperiodic information. In this study, we examined the value of both the periodic and aperiodic components for detecting cognitive deterioration in neurological diseases. To explore the value of these markers, EEG data from two different diseases - Alzheimer's disease (AD) and multiple sclerosis (MS) - were analyzed. The classification results varied for each disease (87% accuracy for AD and 66.7% for MS), indicating an intrinsic difference in classification tasks. Additionally, the aperiodic information showed a better performance in our classification tasks when we calculated it across a wider frequency band. Furthermore, topographic EEG feature maps showed that cognitive deterioration was associated with a steeper 1/f slope in multiple brain regions.